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17 March 2023 How to assess the realism of synthetic spectral images
Marco Hübner, Leonardo Ayala, Maike Rees, Tim J. Adler, Kris Dreher, Silvia Seidlitz, Jan Sellner, Ahmad Bin Qasim, Alexander Seitel, Alexander Studier-Fischer, Alexey Aksenov, Christina Engels, Dogu Teber, Beat Müller-Stich, Felix Nickel, Lena Maier-Hein
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Proceedings Volume PC12361, Molecular-Guided Surgery: Molecules, Devices, and Applications IX; PC1236104 (2023) https://doi.org/10.1117/12.2648461
Event: SPIE BiOS, 2023, San Francisco, California, United States
Abstract
Simulations are indispensable in the field of biomedical optical imaging, particularly in functional imaging. Given the recent rise of artificial intelligence and the lack of labeled in vivo data, synthetic data is not only important for the validation of algorithms but also crucial for training machine learning methods. To support research based on synthetic data, we present a new framework for assessing the quality of synthetic spectral data. Experiments with more than 10,000 hyperspectral in vivo images obtained from multiple species and various organ classes indicate that our framework could become an important tool for researchers working with simulations.
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Marco Hübner, Leonardo Ayala, Maike Rees, Tim J. Adler, Kris Dreher, Silvia Seidlitz, Jan Sellner, Ahmad Bin Qasim, Alexander Seitel, Alexander Studier-Fischer, Alexey Aksenov, Christina Engels, Dogu Teber, Beat Müller-Stich, Felix Nickel, and Lena Maier-Hein "How to assess the realism of synthetic spectral images", Proc. SPIE PC12361, Molecular-Guided Surgery: Molecules, Devices, and Applications IX, PC1236104 (17 March 2023); https://doi.org/10.1117/12.2648461
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KEYWORDS
Monte Carlo methods
Diffuse reflectance spectroscopy
In vivo imaging
Data analysis
Evolutionary algorithms
Functional imaging
Hyperspectral imaging
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